Evidence map›Paper›PMID 39166764›Full record

ArticleClinical and translational gastroenterology2025

A Brief Model Evaluated Outcomes After Liver Transplantation Based on the Matching of Donor Graft and Recipient.

Yuancheng Li, Xingchao Liu, Chengcheng Zhang, Ran Tao, Bi Pan, Wei Liu, Di Jiang, Feng Hu, Zeliang Xu, Dehong Tan and 4 more

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in Clinical and translational gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Yuancheng LiDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Xingchao LiuDepartment of Hepatobiliary Surgery, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Chengcheng ZhangDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Ran TaoDepartment of Organ Transplantation, Liaocheng People's Hospital, Liaocheng, China.
Bi PanDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Wei LiuDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Di JiangDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Feng HuDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Zeliang XuDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Dehong TanDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Yanjiao OuDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Xun LiDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Yuemei YouDepartment of Surgery and Anesthesiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Leida ZhangDepartment of Hepatobiliary Surgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.

Funding

National Natural Science Foundation of China 82270687
6 · The paper itself

Abstract

introductionA precise model for predicting outcomes is needed to guide perioperative management. With the development of the liver transplantation (LT) discipline, previous models may become inappropriate or noncomprehensive. Thus, we aimed to develop a novel model integrating variables from donors and recipients for quick assessment of transplant outcomes.

methodsThe risk model was based on Cox regression in a randomly selected derivation cohort and verified in a validation cohort. Perioperative data and overall survival were compared between stratifications grouped by X-tile. Receiver-operating characteristic curve and decision curve analysis were used to compare the models. Violin and raincloud plots were generated to present post-LT complications distributed in different stratifications.

resultsOverall, 528 patients receiving LT from 2 centers were included with 2/3 in the derivation cohort and 1/3 in the validation cohort. Cox regression analysis showed that cold ischemia time (CIT) ( P = 0.012) and Model for End-Stage Liver Disease (MELD) ( P = 0.007) score were predictors of survival. After comparison with the logarithmic models, the primitive algorithms of CIT and MELD were defined as the CIT-MELD Index (CMI). CMI was stratified by X-tile (grade 1 ≤1.06, 1.06 < grade 2 ≤ 1.87, grade 3 >1.87). In both cohorts, CMI performed better in calculating transplant outcomes than the balance of risk score, including perioperative incidents and prevalence of complications. DISCUSSION: The model integrating variables from graft donors and recipients made the prediction more accurate and available. CMI provided new insight into outcome evaluation and risk factor management of LT.

Indexed as

End Stage Liver DiseaseLiver TransplantationPostoperative ComplicationsAdultCold IschemiaFemaleHumansMaleMiddle AgedProportional Hazards ModelsRetrospective StudiesRisk AssessmentRisk FactorsROC CurveSeverity of Illness IndexTissue Donors

Identifiers

PMID39166764
PMCPMC11756882

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